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Therefore, the issues about data privacy of the published personal information have become a challenging problem. Most of the existing methods focus on cryptography\u2010based techniques by encrypting the sensitive data before publishing. However, these techniques are either too computation expensive or only some authorized users can get access to the encrypted cloud data. The consequence is that the search response time is not satisfactory and the sharing extent of the cloud data is becoming limited. Motivated by this, we propose a perturbation\u2010based method to preserve the privacy of data in cloud. To accelerate the query processing without privacy breaches, a high\u2010efficiency multi\u2010dimensional index is built for answering range counting queries under differential privacy, which embeds privacy\u2010preserving <jats:italic>R\u2010tree<\/jats:italic> index in Content Addressable Network. Experimental results demonstrate that our methods not only protect data privacy in different degree, but also accelerate the query speed efficiently. Compared with the existing method <jats:italic>Quad\u2010opt<\/jats:italic>, our method provides about 20% better data utility under the same differential privacy principles.<\/jats:p>","DOI":"10.1002\/cpe.5458","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T00:44:10Z","timestamp":1565311450000},"update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A multi\u2010dimensional index for privacy\u2010preserving queries in cloud computing"],"prefix":"10.1002","volume":"33","author":[{"given":"Hui","family":"Xu","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology Huazhong University of Science and Technology  Wuhan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-5054-8515","authenticated-orcid":false,"given":"Xiaofeng","family":"Ding","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology Huazhong University of Science and Technology  Wuhan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-3934-7605","authenticated-orcid":false,"given":"Hai","family":"Jin","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology Huazhong University of Science and Technology  Wuhan China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Yu","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology Huazhong University of Science and Technology  Wuhan China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,8,8]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"crossref","unstructured":"YuS WangC RenK LouW.Achieving secure scalable and fine\u2010grained data access control in cloud computing. 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